MRI has become an indispensible resource in clinical medicine because of its non-invasiveness and excellent contrast between soft tissues without using ionizing radiation. From the clinical perspective, MRI still faces significant challenges. First, a strong magnet is usually required to generate a sufficient magnetization to be detected by NMR techniques. The price of a strong magnet (1.5 T and above) constitutes a major part of the cost of an MRI system. Its weight also excludes MRI applications in a mobile or remote setting, such as ambulance, space station, or battlefield. Obese patients cannot obtain MRI due to the limitation of the bore size of the magnet (the maximal bore diameter is around 70 cm). Second, because of potential mechanical or electrical hazards, taking MRI from patients with metallic or electronic objects is difficult. However, imaging patients with wounds caused by metallic objects or with interventional devices (for example, in the intensive care unit or the emergency room) is clinically desirable.
Ultra low field (ULF) MRI has been developed as a potential solution to mitigate the above-mentioned challenges; ULF-MRI systems use magnetic field strength in the range of microteslas to milliteslas, making possible instrumentation at low cost, light weight, and open access. ULF-MRI systems have the advantages of metal compatibility and high T1 contrast; however, one major technical challenge of ULF MRI is its low signal-to-noise ratio (SNR). To address this issue, it has been suggested to separately use a stronger pre-polarization magnet (in the range of tens of milliteslas) for magnetization generation while a weaker signal detection magnet (in the range of tens of microteslas) is used for magnetization precession. Additionally, highly sensitive superconducting quantum interference devices (SQUIDs) are typically used to detect the weak magnetic fields; a SQUID array with up to tens and even hundreds of sensors can be used in an ULF-MRI system for signal detection. Even with the two above-mentioned techniques, the signal to noise ratio of the measurement of an ULF MRI is still needed to be improved. Therefore, by means of signal processing, the present invention intends to suppress the noise in the measurement from a multi-channel MRI system and reinforce the consistency of the measured data.